1. Field
The systems and methods described below relate to the measurement and display of objects of interest in a medical image, and more specifically to automatic measurement and display of attributes of lesions in mammography images.
2. Background
Medical imaging is the field of creating images of the human body for medical purposes, such as diagnosing or examining disease or other physiological anomalies. Numerous types of image modalities produce medical images, such as magnetic resonance imaging (MRI), radiography (x-rays), computed tomography (CT), ultrasound (US) and others. In medical imaging, an object of interest is usually selected pertaining to an area of the human body, such as the head, heart or chest.
One type of medical imaging is mammography, which is the examination of a medical image of the human breast. Mammography is used to detect breast cancer by examining the breast tissue for abnormalities such as lesions that represent microcalcifications or uncharacteristic masses.
In the process of reading digital mammography images, a user, such as a radiologist, often needs to measure attributes of the lesions, such as the location, size, number and distance from other anatomical features. These measurements are then compiled into a report that describes the radiologist's findings. However, these attributes are measured manually by the radiologist, which slows down the workflow and increases the work load of the radiologist.
The radiologist may also need to identify the location of a lesion in terms of standard zones of a breast area illustrated by the breast diagram 10 depicted in FIG. 1—subareolar zone 12, anterior zone 14, middle zone 16 and posterior zone 18. FIG. 1 depicts a left and right breast, but only the breast on the right side of the image is labeled in the figure. Similar labels apply for the breast on the left side. FIG. 1 also illustrates a breast diagram as seen from a cranio-caudal (CC) view, where the breast area can be further classified into a lateral zone 20, central zone 22 and medial zone 24. In a medio-lateral (ML) or medio-lateral oblique (MLO) view of a breast area depicted by the breast diagram 26 shown in FIG. 2, the lesion can be further classified as belonging to a superior zone 28 or inferior zone 30. Furthermore, the radiologist may want to determine a quadrant and clock location of a lesion when both the CC and ML/MLO view images are available, as illustrated by the breast diagram 32 in FIG. 3 of a left breast 32a and right breast 32b. The quadrant locations in a quadrant/clock location diagram are upper outer 34, upper inner 36, lower outer 38 and lower inner 40, and the clock positions 42 correspond to a conventional analog clock face, with positions ranging from 1-12.
For all of the illustrated lesion location schemes, the radiologist must manually determine the zones, quadrant and clock positions on the breast area of a mammography image and then determine which zone, quadrant and clock position the lesion falls into. If the lesion is palpable, the position of the lesion can be determined directly on the breast. Otherwise, using the nipple's location as the reference, the radiologist can determine whether a lesion is in the inner or outer zone in the breast by checking the position of the lesion in the CC view image; and determine whether a lesion is in the upper or lower zone by checking the position of the lesion in the ML/MLO view image. Then the quadrant can be determined jointly from the upper/lower and outer/inner position. After determining the quadrant, the radiologist can further estimate the clock position by checking whether the lesion is closer to the uppermost (lowermost) or innermost (outermost) part of the breast. The process is time consuming. Moreover, as the radiologist interprets the location information from two projection images empirically, the results may have a high inter-person variation.
Thus, there is an unmet need to develop systems and methods for effectively and efficiently measuring and displaying attributes of lesions or other objects of interest in medical images.